Simulation study of frequency estimators

We develop a frequency estimator employing Kalman filter algorithm for rapid online frequency estimation in both additive white Gaussian noise channel and static fading channel. A new measurement model is proposed, which can describe the phase noise more accurately, thus improves the performance by 4 dB in the initial acquisition stage. Simulations show that the proposed estimator is unbiased and efficient. The proposed frequency estimator can incorporate extra a priori information, thus provides superior performance compared to some Maximum Likelihood estimators available. In the static fading channel, diversity technique can be easily incorporated to improve the performance of the proposed frequency estimator.

Author dc:creator

• WU QIONG

• Kalman fitler, Frequency, Estimation, Synchronization, Fading channel, Additive white Gaussian noise channel